The open-source AI Agent Cloud — a secure, isolated cloud computer for every AI agent
HQ: San Francisco, CA, United States | Founded: 2022 | Employees: Seed/A-stage team growing engineering, product and GTM in San Francisco | Stage: Series A ($21M, July 2025); ~$32M+ total raised per company | Website: https://e2b.dev
E2B builds cloud infrastructure for AI agents: secure, isolated, instantly-available computers that agents can use to do real work. An agent working through E2B gets its own sandboxed machine — Linux environments with code execution, filesystems, browsers, and tooling — spun up in milliseconds via a simple SDK. Because every session is isolated, agent actions can't touch the host or each other, which is what makes the difference between a demo and enterprise deployment.
The company was founded in 2022 by Vasek Mlejnsky and Tomas Valenta, two Czech builders who moved to San Francisco as the agent wave hit. Mlejnsky (CEO) and Valenta (CTO) started E2B as an open-source code-interpreter sandbox for LLMs and expanded it into a full agent-runtime platform. The open-source core is the distribution engine: the SDKs (Python and JavaScript) are embedded across the agent-framework ecosystem, from LangChain to custom harnesses.
By mid-2025 the platform had become the de facto sandbox standard: hundreds of millions of sandbox sessions since October 2024, 88% of the Fortune 100 signed up, and marquee users including Hugging Face, LMArena, Perplexity, Lindy, Groq, and Manus. Enterprises use E2B for everything from data-analysis agents that execute Python, to QA agents, to reinforcement-learning environments for model training.
The roadmap is explicitly standard-setting: E2B wants to be a universal interface for agent compute — Linux interpreters, Windows VMs, browser environments — deployable on Kubernetes, AWS, GCP, Azure, Cloudflare, or in-house VPCs, with pluggable enterprise modules (secrets vault, observability, shared context). The analogy the founders use: agents will be as commonplace as iPhone apps, and every app needs iOS.
E2B is betting that every AI agent needs what every iPhone app needs: an operating environment. A language model that can only chat is a parlor trick; an agent that can run code, install packages, browse the web, and inspect files in its own secure machine is software. E2B's insight was to make that machine boringly easy — one SDK call spins up an isolated sandbox in milliseconds, in the cloud or inside a company's own AWS/GCP/Azure account — and to make it open source, so it became the default everyone builds against.
The adoption curve tracks the agent boom almost perfectly. Since late 2024 the platform has run hundreds of millions of sandbox sessions, and by its July 2025 Series A the company reported 88% of the Fortune 100 signed up and more than half the Fortune 500 using it. The name-drops are the agent ecosystem's who's-who: Hugging Face and LMArena run tens of thousands of concurrent E2B machines for research; Perplexity and Lindy build agentic features on it; Groq uses it for code execution; Manus — the viral agent of early 2025 — runs its virtual computers on E2B. When nearly every major agent team converges on the same plumbing, the plumbing becomes the standard.
The company is now pushing up the stack with what it calls the Enterprise AI Agent Cloud: sandbox observability for compliance, a secrets vault for credentials, shared persistent state, and self-hosting in customer VPCs for regulated industries. The strategic tension is the classic infrastructure one — hyperscalers and platform vendors could bundle 'good-enough' sandboxes, and per-second compute is a commoditized resource. But E2B's open-source distribution, its head start with the most demanding agent teams, and its position as the neutral layer (agent frameworks above it, clouds below it) give it the same shape of opportunity Docker and Vercel rode: own the developer-facing interface to a resource everyone needs.
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